Update app.py

app.py

@@ -1,16 +1,25 @@
 import streamlit as st
 import pandas as pd
+import os
 from huggingface_hub import InferenceClient
 
 # Initialize HF Inference client
 @st.cache_resource
 def get_client():
-    return InferenceClient(token=st.secrets["HF_TOKEN"])
+    # Try to get token from environment variables (works in Hugging Face Spaces)
+    hf_token = os.environ.get("HF_TOKEN")
+    if not hf_token:
+        try:
+            hf_token = st.secrets["HF_TOKEN"]  # Fallback to Streamlit secrets
+        except:
+            st.error("HF_TOKEN not found. Please set it in your Space's settings or secrets.toml")
+            st.stop()
+    return InferenceClient(token=hf_token)
 
 client = get_client()
 
 # Define the LLM call function
-def call_llama(prompt, model="meta-llama/Meta-Llama-3-8B-Instruct", max_tokens=500):
+def call_llama(prompt, model="mistralai/Mistral-7B-Instruct-v0.2", max_tokens=500):
     try:
         response = client.text_generation(
             prompt=prompt,
@@ -33,7 +42,7 @@ with st.sidebar:
         st.markdown("""
             # 🦙🦙 Duel Agent Simulation
             ## Overview
-            This app simulates an interview with two Llama3 AI agents:
+            This app simulates an interview with two AI agents:
             1. **Interviewer**: Asks questions about your topic
             2. **Interviewee**: Attempts to answer (poorly at first)
             3. **Judge**: Provides feedback after each answer
@@ -110,15 +119,12 @@ if submit_button:
                 st.markdown(f"**Interviewee:** {answer}")
             st.session_state.messages.append({"role": "user", "content": f"Interviewee: {answer}"})
             
-            # Judge evaluates - FIXED STRING FORMATTING HERE
+            # Judge evaluates
             feedback_prompt = f"""Evaluate this interview exchange:
                                 Question: {question}
                                 Answer: {answer}
                                 Provide specific feedback and a score from 1-10 (10=best). 
-                                Format your response as: 
-                                "Feedback: [your feedback here] 
-                                Score: [number between 1-10]"
-                                """
+                                Format: Feedback: [your feedback] Score: [1-10]"""
             
             judge_response = call_llama(feedback_prompt).strip()